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OpenTrials
Completed

NCT Number: NCT02581514

Eosinophilia Diagnosis

Eosinophilia, defined by a blood eosinophil granulocytes rate greater than 500 / mm3, is frequently encountered in internal medicine.

Its causes are varied: atopy, drug allergies, parasitic infections, autoimmune diseases and solid neoplasias. Over 200 etiologies have been reported, some difficult to diagnose and can be life-threatening Eosinophilia can be a diagnostic dilemma, as the etiologies are extensive and varied.

The aim of this study is to assess the feasibility of a diagnostic approach based on a decision algorithm in a group of patients with eosinophilia.

We assume that a procedure with a hierarchy of additional tests would increase the frequency of diagnosed cases while decreasing the time to diagnosis.

This procedure defined by an algorithm would even reduce the number of tests necessary to reach a diagnosis.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Médecine Interne A

Limoges, 87000, France

About this study

Eosinophilia, defined by a blood eosinophil granulocytes rate greater than 500 / mm3, is frequently encountered in internal medicine.

Its causes are varied: atopy, drug allergies, parasitic infections, autoimmune diseases and solid neoplasias. Over 200 etiologies have been reported, some difficult to diagnose and can be life-threatening

Eosinophilia can be a diagnostic dilemma, as the etiologies are extensive and varied.

The aim of this study is to assess the feasibility of a diagnostic approach based on a decision algorithm in a group of patients with eosinophilia.

The contribution to the diagnosis of a hierarchical strategy for prescribing additional tests , based on clinical examination as well as some simple diagnostic tests, has never been evaluated

We assume that a procedure with a hierarchy of additional tests would increase the frequency of diagnosed cases while decreasing the time to diagnosis.

This procedure defined by an algorithm would even reduce the number of tests necessary to reach a diagnosis.

All types of patients are tacked into account: those coming from the university hospital, referred by general practitioners or by other hospitals.

In addition we address the internal medicine patients ,but also those of Hematology and Infectious Diseases. A comparison of these various groups would be relevant, since disorders that may be different.

Once enrolled, the patient is drived by the investigator through the various steps and exams imposed by the algorithm.

Indeed, during 5 months (Day1 5, 43, 71 , 85 , 99 ,113 and month 5), patient is asked to comply to the various exams and assessment imposed by the algorithm and that should lead to a diagnosis

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patient having one of the three following criteria:
  • hypereosinophilia> 1500 / mm3, checked on at least two samples (interval between 2 samples at the discretion of the clinician)
  • or hypereosinophilia> 500 cells / mm3 and organ damage with infiltration NCB proven by pathological examination,
  • or hypereosinophilia> 500 cells / mm3 and found consistently for at least six months (present on all controls carried out before inclusion).
  • Patient affiliated or beneficiary of a social security system
  • Patient who signed the informed consent

Exclusion criteria

  • Patient with solid tumors known (under chemotherapy or planned)
  • Patient unable to understand or to adhere to the Protocol
  • Patient unable to give consent
  • Pregnant or breastfeeding women
  • Patient already participating in an interventional trial

Treatment and study plan

Scheduled exams and diagnosis

Other

Scheduled exams and diagnosis circuit as imposed by the algorithm

Primary outcomes

  1. Number of patients having correctly follow the diagnosis algorithm

    Time frame: 5 months

    This outcome measure how many patients have correctly followed the diagnosis algorithm

Secondary outcomes

  1. Rate of diagnosis

    Time frame: 5 months

    Evaluate the rate of diagnosis using our diagnosis algorithm

  2. Assess the time to diagnosis

    Time frame: 5 months

    Assess the time to diagnosis

  3. Description of diagnosis

    Time frame: 5 months

    To compare the diagnosis found in our study to the published cohort.

Sponsors and collaborators

Lead sponsor

University Hospital, Limoges

Other

Registry information

Official study title

Algorithm for the Early Diagnosis and Treatment of Patients With Eosinophilia

Acronym: EOSINOPHILIM

Important dates

Study start
2015
Primary completion
2019
Study completion
2021
First posted
Oct 21, 2015
Registry last updated
Jun 24, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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